--- task_categories: - text-classification --- # AutoTrain Dataset for project: twitter-goemotions-binary-fear-classification ## Dataset Description This dataset has been automatically processed by AutoTrain for project twitter-goemotions-binary-fear-classification. ### Languages The BCP-47 code for the dataset's language is unk. ## Dataset Structure ### Data Instances A sample from this dataset looks as follows: ```json [ { "text": "Downvoting comments you don't like is your right.", "feat_id": "ed62dkv", "feat_author": "128bitworm", "feat_subreddit": "im14andthisisdeep", "feat_link_id": "t3_ac6bna", "feat_parent_id": "t1_ed5trip", "feat_created_utc": 1546542336.0, "feat_rater_id": 35, "feat_example_very_unclear": false, "feat_admiration": 0, "feat_amusement": 0, "feat_anger": 0, "feat_annoyance": 0, "feat_approval": 0, "feat_caring": 0, "feat_confusion": 0, "feat_curiosity": 0, "feat_desire": 0, "feat_disappointment": 0, "feat_disapproval": 1, "feat_disgust": 0, "feat_embarrassment": 0, "feat_excitement": 0, "target": 0, "feat_gratitude": 0, "feat_grief": 0, "feat_joy": 0, "feat_love": 0, "feat_nervousness": 0, "feat_optimism": 0, "feat_pride": 0, "feat_realization": 0, "feat_relief": 0, "feat_remorse": 0, "feat_sadness": 0, "feat_surprise": 0, "feat_neutral": 0 }, { "text": "I fucking love this", "feat_id": "edxv95q", "feat_author": "fueryerhealth", "feat_subreddit": "FellowKids", "feat_link_id": "t3_af72i1", "feat_parent_id": "t3_af72i1", "feat_created_utc": 1547342464.0, "feat_rater_id": 19, "feat_example_very_unclear": false, "feat_admiration": 1, "feat_amusement": 0, "feat_anger": 0, "feat_annoyance": 0, "feat_approval": 0, "feat_caring": 0, "feat_confusion": 0, "feat_curiosity": 0, "feat_desire": 0, "feat_disappointment": 0, "feat_disapproval": 0, "feat_disgust": 0, "feat_embarrassment": 0, "feat_excitement": 0, "target": 0, "feat_gratitude": 0, "feat_grief": 0, "feat_joy": 0, "feat_love": 1, "feat_nervousness": 0, "feat_optimism": 0, "feat_pride": 0, "feat_realization": 0, "feat_relief": 0, "feat_remorse": 0, "feat_sadness": 0, "feat_surprise": 0, "feat_neutral": 0 } ] ``` ### Dataset Fields The dataset has the following fields (also called "features"): ```json { "text": "Value(dtype='string', id=None)", "feat_id": "Value(dtype='string', id=None)", "feat_author": "Value(dtype='string', id=None)", "feat_subreddit": "Value(dtype='string', id=None)", "feat_link_id": "Value(dtype='string', id=None)", "feat_parent_id": "Value(dtype='string', id=None)", "feat_created_utc": "Value(dtype='float32', id=None)", "feat_rater_id": "Value(dtype='int32', id=None)", "feat_example_very_unclear": "Value(dtype='bool', id=None)", "feat_admiration": "Value(dtype='int32', id=None)", "feat_amusement": "Value(dtype='int32', id=None)", "feat_anger": "Value(dtype='int32', id=None)", "feat_annoyance": "Value(dtype='int32', id=None)", "feat_approval": "Value(dtype='int32', id=None)", "feat_caring": "Value(dtype='int32', id=None)", "feat_confusion": "Value(dtype='int32', id=None)", "feat_curiosity": "Value(dtype='int32', id=None)", "feat_desire": "Value(dtype='int32', id=None)", "feat_disappointment": "Value(dtype='int32', id=None)", "feat_disapproval": "Value(dtype='int32', id=None)", "feat_disgust": "Value(dtype='int32', id=None)", "feat_embarrassment": "Value(dtype='int32', id=None)", "feat_excitement": "Value(dtype='int32', id=None)", "target": "ClassLabel(names=['0', '1'], id=None)", "feat_gratitude": "Value(dtype='int32', id=None)", "feat_grief": "Value(dtype='int32', id=None)", "feat_joy": "Value(dtype='int32', id=None)", "feat_love": "Value(dtype='int32', id=None)", "feat_nervousness": "Value(dtype='int32', id=None)", "feat_optimism": "Value(dtype='int32', id=None)", "feat_pride": "Value(dtype='int32', id=None)", "feat_realization": "Value(dtype='int32', id=None)", "feat_relief": "Value(dtype='int32', id=None)", "feat_remorse": "Value(dtype='int32', id=None)", "feat_sadness": "Value(dtype='int32', id=None)", "feat_surprise": "Value(dtype='int32', id=None)", "feat_neutral": "Value(dtype='int32', id=None)" } ``` ### Dataset Splits This dataset is split into a train and validation split. The split sizes are as follow: | Split name | Num samples | | ------------ | ------------------- | | train | 168979 | | valid | 42246 |